Why fashion retailers need to look at auto-tagging solution as an indispensable element of effective eCommerce catalog management
Catalog management is a dynamic process where products are organized in a specific way. The more organized a catalog’s data is, the more it helps businesses in marketing their products across platforms and expands product discovery, which is an avenue for sales conversion. Tags offer a flexible way to organize it. Hence the importance of assigning relevant tags and keywords to all product images of catalogue in undoubtful. But the process of assigning tags in a product catalog tends to be slow and not a very accurate manual job.
One of the challenges of marketplaces or eCommerces with thousands or millions of products is the image tagging task. The growth in the number of products being sold online and the relative heterogeneity in the categories of these products has become physically impossible and infeasible to manually tag them. Using auto-tagging exclusively provides several benefits over manual tagging: saving you a lot of time and effort!
Additionally, there are as many tagging criteria as perceptions. In other words, not everyone will tag the same images with the same tags. This leads to discrepancy in the kinds of tags allotted to the products which minimizes the capacity of searchability of products. And meeting the need of users to be accurate in taking them to the right product is essential.
An automatic image tagging system like Wide Eyes’ Auto-tagging API can help take care of both of these problems and build an efficient product tagging system even if the database consists solely of visual information about the products. Wide Eyes’ automated solution will set homogenous tags around the whole catalogue. For these reasons the smart organizations are using AI-powered visual recognition technology to automatically extract product attributes from fashion images.
How does Wide Eyes’ auto-tagging work?
(Single API – 24h integrations)
Fashion images are processed through our Auto-Tagging API, in a matter of thousands of a second, we analyze them and suggest automatically high quality tags they should be associated with.
Our powerful and accurate image tagging API, based on advanced image recognition algorithms, can automatically assign tags to every trending item that appears in the image, including tags that make the difference based on visual characteristics; because details do matter in fashion.
Up to 97% accuracy
We aim at achieving the highest possible precision rates. As some photos and images might be very complex even for the human brain to identificate, it’s not a surprise that our technology can’t guarantee 100% precision rate. However, we very often get to the 85-97% range in terms of accuracy rates, depending on the complexity of the images.
More than 750 visual data points considered to driving better conversion and customer engagement
Currently, we can analyze more than 750 data points per image. We are able to automatically “read” from an image not only colour and category as many companies do, we are going deeper by detecting type of collar, sleeve length, silhouette of dresses, skirts, pants, platforms, heels and height for shoes and many more. Every category has its own set of rich and detailed tags to be applied. We’re constantly adding more tags to keep up with the latest fashion trends.
Conclusion…
Automating the product tagging process, retailers save time and costs, and improve efficiency in catalog management – from product upload and right categorization to SEO and product ranking.
The auto-tagging based on visual features is helping to index the products better leading to more accurate searches on the site. The more relevant tags a product image has, the greater probability it has to appear in specific search results from shoppers.
Wide Eyes’ Auto-tagging API is easy to implement, in less than 24 hours it could be in full production. If you want to know how to set up our auto-tagging API, contact us!
